MS SQL Server for instance comes with its own profiler. You can look for slow queries, then try to understand why by getting the query execution plan. You can a

MS SQL Server for instance comes with its own profiler. You can look for slow queries, then try to understand why by getting the query execution plan. You can alternatively also look for queries with a high standard deviation, which can hint of queries that get slower as there are more rows associated with a user. Once you have the execution plan, you can either optimize the query, optimize the schema (add indices), or simply optimize the application (e.g: narrow the scope of the query, reduce call count). That however, won't allow you to horizontally scale. The only realistic way to horizontally scale is sharding. Replication will slow down your writes as more machines are added and that simply does not scale. Using the same database for everything and everyone is a lousy way to go. Eventually you will need to keep things on different machines at some point. Then, don't put large blobs into a database and store just the blob IDs in your database. Use another data store for that. Analytics, logging, etc doesn't belong into an OLTP database. Use another database for that not your OLTP one.